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TensorRT OSS v8.2.0 EA

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@rajeevsrao rajeevsrao released this 05 Oct 19:03
· 2 commits to master since this release

TensorRT OSS release corresponding to TensorRT 8.2.0.6 EA release.

Added

  • Demo applications showcasing TensorRT inference of HuggingFace Transformers.
    • Support is currently extended to GPT-2 and T5 models.
  • Added support for the following ONNX operators:
    • Einsum
    • IsNan
    • GatherND
    • Scatter
    • ScatterElements
    • ScatterND
    • Sign
    • Round
  • Added support for building TensorRT Python API on Windows.

Updated

  • Notable API updates in TensorRT 8.2.0.6 EA release. See TensorRT Developer Guide for details.
    • Added three new APIs, IExecutionContext: getEnqueueEmitsProfile(), setEnqueueEmitsProfile(), and reportToProfiler() which can be used to collect layer profiling info when the inference is launched as a CUDA graph.
    • Eliminated the global logger; each Runtime, Builder or Refitter now has its own logger.
    • Added new operators: IAssertionLayer, IConditionLayer, IEinsumLayer, IIfConditionalBoundaryLayer, IIfConditionalOutputLayer, IIfConditionalInputLayer, and IScatterLayer.
    • Added new IGatherLayer modes: kELEMENT and kND
    • Added new ISliceLayer modes: kFILL, kCLAMP, and kREFLECT
    • Added new IUnaryLayer operators: kSIGN and kROUND
    • Added new runtime class IEngineInspector that can be used to inspect the detailed information of an engine, including the layer parameters, the chosen tactics, the precision used, etc.
    • ProfilingVerbosity enums have been updated to show their functionality more explicitly.
  • Updated TensorRT OSS container defaults to cuda 11.4
  • CMake to target C++14 builds.
  • Updated following ONNX operators:
    • Gather and GatherElements implementations to natively support negative indices
    • Pad layer to support ND padding, along with edge and reflect padding mode support
    • If layer with general performance improvements.

Removed

  • Removed sampleMLP.
  • Several flags of trtexec have been deprecated:
    • --explicitBatch flag has been deprecated and has no effect. When the input model is in UFF or in Caffe prototxt format, the implicit batch dimension mode is used automatically; when the input model is in ONNX format, the explicit batch mode is used automatically.
    • --explicitPrecision flag has been deprecated and has no effect. When the input ONNX model contains Quantization/Dequantization nodes, TensorRT automatically uses explicit precision mode.
    • --nvtxMode=[verbose|default|none] has been deprecated in favor of --profilingVerbosity=[detailed|layer_names_only|none] to show its functionality more explicitly.

Signed-off-by: Rajeev Rao [email protected]